A Conversation With Leading AI Expert Kurt Kendall On Leveraging Disruptive Technologies To Drive Growth

Founded in 2010 by the president and CEO Jaswinder (Jassi) Chadha, who recognised a gap in the life sciences market for data-driven solutions, Axtria seamlessly provides enterprise-grade analytics on integrated software technologies. Today’s news represents an important step in enabling some of our most critical government agencies to benefit from access to industry-leading open-source AI models to build on and iterate on. The global competition in open-source AI from China only reaffirms the importance of the U.S. government partnering with industry-leading American companies to ensure that the government has the best resources at its disposal to build on.

Traditionally, creating 3D animations involves a labor-intensive process of manual modeling and rigging, but Wonder’s AI capabilities significantly cut down on that workload. Animators can now capture real-world motion, such as a dancer’s performance or an outdoor landscape, and instantly convert it into a manipulatable 3D scene. Game developers, for instance, can use Wonder to create realistic environments, like bustling cityscapes or natural settings, directly from video footage.

He urged organizations not to overprioritize on productivity measures, and said the expertise of senior developers matters more than ever, as they need to cultivate junior developers. Echoing back to the keynote, he noted that today’s AI code assistants are focused on little things, and show lots of promise, but also lots of disappointment. He notes that in some large organizations, software designed by the code assistants have completion acceptance rates of less than 30%.

Llama’s adaptability in high-stakes environments demonstrates its capability to provide crucial insights for national defense. Michael J. Miller is chief information officer at Ziff Brothers Investments, a private investment firm. From 1991 to 2005, Miller was editor-in-chief of PC Magazine,responsible for the editorial direction, quality, and presentation of the world’s largest computer publication. Miller works separately for a private investment firm which may at any time invest in companies whose products are discussed, and no disclosure of securities transactions will be made. “It’s not just about how we build software, it’s about what kind of software we build,” according to Walsh, noting that only 54% of AI projects are successfully deployed. He added that this will require a new breed of software professional – the AI engineer.

With its innovative design, Clone Robotics is setting a new benchmark in the development of humanoid robotics, and it will be exciting to see how these technologies evolve. More than that, it can be a differentiator, setting companies apart in a market increasingly aware of ethical issues. By building a strong set of principles from the start, companies—whether start-ups or established enterprises—can create trust and credibility, two invaluable assets in today’s digital age. What’s missing from many of the discussions on AI is where the “returns” on the investments will come from.

Why Meta, And Why Now?

Unlike many public AI models that are trained on vast, open datasets, Vertex AI’s Grounding feature ensures that data stays secure and outputs are uniquely tailored. Moreover, with the addition of integration capabilities like the Gemini API, companies can take advantage of Google’s extensive search capabilities to enhance the AI’s understanding of context. What AI is now starting to enable is the ability to directly measure and understand attitudes and emotions. To build insights around emotions, you need to be able to work with data sets of language, imagery, and sound. The classical data science algorithms did a poor job of mining these data sets for emotions. But Gen AI’s purpose is built for understanding and communicating with these unstructured data types.

Not surprisingly, AI was a major theme at Gartner’s annual Symposium/IT Expo in Orlando last week, with the keynote explaining why companies should focus on value and move to AI at their own pace. But I was more interested in some of the smaller sessions where they focused on more concrete examples, from when not to use generative AI to how to scale and govern the technology to the future of AI. As corporates and enterprises awaken to responsible AI, they’re leveraging their scale and resources to set the bar high, not just for compliance, but for genuinely ethical practices within their organisations and technological partners. The challenge isn’t just about building smarter algorithms, it’s about embedding values into the technology we create — it’s starting a conversation that many tech innovators might find uncomfortable, but necessary. For startups aiming to scale and partner with established corporations, building ethically and responsibly with AI is not just smart — it’s crucial and could become their greatest differentiator. By integrating design language into its generative process, Recraft AI helps streamline creative tasks while supporting innovation across various fields.

Opening Up Llama For National Security Uses

If you are going to use AI to write your resume, make it the skeleton on which you build your human insight, creativity, personalization and tailoring, and unique experiences to convey your passion for the role. Unfortunately, AI is trained on a set of data that is not current and evolving with the times. Currently, it cannot be aware of immediate events that could have an impact on you landing your future role, neither is it aware of buzzwords that should be incorporated into your resume. Artificial intelligence is emerging as the hot new trend of the decade, replacing functions and augmenting aspects of work through automation. People are using it for a range of purposes, from performing administrative tasks, to analyzing data, to creating content, to hiring, and even in the steps towards getting hired! Most recently the emergence of ChatGPT has spiked the number of job candidates who have turned to AI to draft resumes, write answers to job application questions, create cover letters, and even prep for interviews.

IBM is actively involved in U.S. defense through various contracts and partnerships aimed at enhancing military and defense capabilities. Additionally, IBM provides cybersecurity services to NATO, helping integrate and configure NATO’s cyberdefense infrastructure. I believe Meta’s commitment to open-source AI is a key differentiator compared to competitors such as OpenAI and Google. While OpenAI and others maintain more closed ecosystems motivated by commercial interests, Meta has embraced an open-source philosophy, allowing enterprises to customize models more easily and avoid vendor lock-in. This approach mirrors Meta’s broader strategy of fostering innovation through openness, as seen with other initiatives like the Open Compute Project and PyTorch.

“We’ve seen some of vendor promises which they are starting to deliver on, and that is going to change the way we think in terms of AI,” he said, suggesting we should think of it like a new “teammate is joining a team.” Yet, he noted the power of simplicity, using the original iPod as an example. If we could get applications that reduce the time you need to spend dealing with the notifications, that would give people more time. Some of that will initially result in productivity leakage, but that will reduce over time.

If we were to ask AI to take control of these interruptions, through various agents, it could be scary. Only after you have your use cases should you build an AI governance structure, with the principles, guides, and standards you need to scale. For this, she said, data will be central to your AI strategy, and she suggested establishing an end-to end AI lifecycle. If you have a framework for developing, delivering, and testing, then you can scale AI with automation. But the key first step is to select and prioritize the use cases that make most sense for your organizations.

Then there is composite AI, which involves assembling multiple AIs together, including older models such as decision intelligence, the gen AI models that are now getting attention, and new things such as neurosymbolic AI. He believes we should be focusing on the second one and pushing for more automation. In general, he proposed an “employee-first approach,” where instead of looking at tasks to automate, we ask people what things they don’t like about their job. This leads to instance acceptance, and then you can move on to the next task and the one after that to result in “empathetic AI.” For much of the everyday AI—applications like coding assistants, ChatGPT, or Copilot for Microsoft 365—using it is just table stakes (not bringing a competitive advantage), and it is typically adopted by only one-third of employees. She noted it’s expensive and hard to calculate the return-on-investment for such applications.

Amazon Web Services And Microsoft Azure: Secure Hosting

Not surprisingly, the cost of building and using AI is another significant hurdle. In a survey by Gartner, more than 90% of CIOS said that managing cost limits their ability to get value from AI. For instance, data preparation and inferencing costs are often greatly underestimated, explained Hung LeHong, a distinguished VP analyst at Gartner. Chandrasekaran pointed out that the market has so far been dominated by closed-source models, but open source provides customization and deployment flexibility — models can run in the cloud, on-prem, at the edge or on mobile devices. Very quickly, the topic of AI agents has moved from ambiguous concepts to reality. Enterprises will soon be able to deploy fleets of AI workers to automate and supplement — and yes, in some cases supplant — human talent.

He built on the discussion from this year’s keynote of deep productivity that results from low-experience workers doing low-complexity tasks and high-experience workers doing high-complexity tasks. AI works great in the zone of deep productivity, he said, noting how Mitsui Chemical discovered 160 new materials that generally create $7 million in value each year. Part of this, she said, is because of where the spending and control of AI projects is happening.

AI is certainly driving great software engineering efficiency, but the very thing that is transforming developer productivity is also transforming what we can do with software, Walsh noted. She said companies should define, develop, and curate a portfolio of AI initiatives, and said that each initiative demands a cost, risk, and value assessment. “You actually need different kinds or specific kinds of governance across the spectrum.” In general, a decision on AI governance isn’t a “one and done” thing, it will change over time. She warned that organizations that solely focus on gen AI increase the risk of failure in their AI projects and may miss out on many opportunities. First, VCs have funded “an enormous amount of startups” — but they have still grossly underestimated the amount of money startups need to be successful. Also, many startups have “very flimsy competitive moats,” essentially serving as a wrapper on top of a model that doesn’t offer much differentiation.

Navy to provide cloud tools and services aimed at modernizing its networks; and the Air Force’s Advanced Battle Management System. Meta has just announced the availability of its open-source Llama models—which I consider to be industry-leading—to U.S. government agencies in the areas of defense and national security, along with their private-sector partners. With China making significant strides in developing its own variants of open-source AI models, it is essential that the U.S. doesn’t fall what is a key differentiator of conversational ai behind and has access to the industry’s most advanced models backed by a strong partner ecosystem. Meta’s move today promotes both U.S. leadership in the international technology landscape and the emergence of what Meta calls “a global open source standard for AI models” on par with Linux and Android. Another standout feature is the use of Neural Engine, Apple’s specialized hardware for machine learning, which plays a key role in delivering these AI capabilities efficiently across devices.

She said it was very good at content generation, knowledge discovery, and conversational user interfaces; but has weaknesses with reliability, hallucinations, and a lack of reasoning. Generative AI is probabilistic, not deterministic, she noted, and said it was at the “peak of inflated expectations” in Gartner’s hype cycle. “Responsible innovation is not about slowing down; it’s about doing things right so that you can speed up sustainably,” said Lucio Ribeiro.

By saving us time by doing some tasks for us, AI will give us more time to think, to thoughtfully decide to act, and to interact with colleagues. She then shared a method for visualizing the cost of gen AI, and said it’s important to monitor costs very carefully, because estimates can be off by 500 to 1,000%. “One of the reasons that governance is so difficult in this market is that for those who are in charge of governance, it’s even unclear what their agreement is with their scope or the scale, or what’s underneath them,” Karamouzis said. That strategy has to be adaptable, she said, with the two key issues being how to set expectations for AI maturity, and when to pivot. Most customers will choose one of the first three of these, he said, but it’s most important to align the choice with the goals of the application. “Agentic AI” from gen AI vendors offers promise for solving some of the issues, but she said this is now just a work-in-process, and she urged attendees to beware of “agent-washing.”

In addition, it lacks a human personality so it will look uncomfortably artificial and in some cases, crowded with too unnecessary verbiage. You cannot communicate your passion for a role or your culture fit for an organization using AI alone. So while we all understand that it’s extremely powerful, its own nature makes it extremely difficult to use it in the context of an enterprise workflow, because enterprise workflows needs to be reliable, deterministic. And our job right now it’s actually to make it exactly as I said, reliable and deterministic and capable of using in an enterprise workflow, and we are going to spend the next few years in order to make it happen. Therapeutic or focused ultrasound began being applied to neurologic conditions less than a decade ago, but its potential in a wide spectrum of brain applications is high.

Three-quarters of CEOs surveyed by Gartner say AI is the technology that will be most impactful to their industry, a significant leap from 21% just in 2023, LeHong pointed out. My overarching message with my discussion of Ensemble AI is that rather than a singular technology solution, many use cases require a combination of technologies all working together, potentially uniquely to the use case. Anyone who’s worked in marketing knows that it takes a lot of different tech components (e.g. the marketing tech stack) to support marketing’s business needs.

He noted that Gartner believes you don’t need a Chief AI Officer, but you do need an AI leader to ensure governance, the use of best practices, and the right competencies. She talked about creating “opportunity radars” of specific applications and shared one in manufacturing. She divided this up into everyday AI and game-changing AI, and external customer-facing and internal operations.

• When we think of artificial intelligence (AI) and innovation, “responsibility” and “ethics” may not be the first words that come to mind.
• Game developers, for instance, can use Wonder to create realistic environments, like bustling cityscapes or natural settings, directly from video footage.
• But that will not stop the huge community of developers who are already familiar with the GitHub experience to try it out, and may be even invite a lot of new coders who have never coded before.
• With five major model releases in less than two years, Meta has made it clear it will invest aggressively to ensure Llama is a leading AI foundation model with a vibrant ecosystem.

Chakraborty suggests shifting from capital to operational expenditures to help solve these investment questions. He also says many organisations are using “innovation budgets” that often have a longer runway for showing returns on investment. In order to do so, please follow the posting rules in our site’s Terms of Service. “Humans have always used tools to augment and enhance their capabilities,” Walsh said, comparing using AI tools to using a hammer, “but all of the intention and all of the agency resides in me.”

This capability brings a new level of utility to ChatGPT, enabling it to answer questions about recent events, trends, or niche topics that are not included in its training data. Companies, and specifically the CEOs leading them, need to have the courage to take risks. OpenAI didn’t become one of the most talked about companies that is now being valued at $150 billion because they took a cautious approach. You can foun additiona information about ai customer service and artificial intelligence and NLP. They took the risk to spend billions of dollars and launched an imperfect product precisely because they wanted to transform the world through AI. I’m not suggesting other companies take on that level of risk but the winners in AI are going to be those companies who best manage through the risk and reward tradeoffs. This is the kind of story that deserves keynote attention – AI agents can share the airtime.

The future of innovation doesn’t have to be a zero-sum game between progress and ethics. Innovation isn’t static — it evolves, and so should our approach to what successful innovation looks like. The key is finding a way to innovate without compromising ethical standards — a balance that requires transparency, accountability, and ongoing dialogue. “Our goal is to enable innovation, but not at the cost of ethics,” he emphasised. Lucio Ribeiro has led the marketing, digital and innovation team at Seven and Optus and co-hosts the InnovAItors series. “Autonomous agents are one of the hottest topics and perhaps one of the most hyped topics in gen AI today,” Gartner distinguished VP analyst Arun Chandrasekaran said at the Gartner Symposium/Xpo this past week.

Apple’s AI models process data directly on the device whenever possible, ensuring that personal information stays under the user’s control. This on-device approach contrasts sharply with the cloud-based AI models from other tech giants, which often require internet connectivity and may involve sending sensitive data to remote servers. By handling AI tasks locally, Apple not only offers a fast and responsive user experience but also builds on its promise of maintaining user privacy.

This is a huge step forward compared to most industrial robots, which tend to operate in a rigid, pre-programmed manner. Additionally, the robot’s use of AI models for processing sensory input means it can adapt its actions in real time, a feature that makes it far more flexible compared to traditional robotic arms. He noted that augmentation is nice, but the real move will be in offloading entire aspects of tasks, so that humans can focus on doing higher level tasks. To do this, companies are proposing AI agents that will have to become more like a teammate. He said software agents that bridge the gap between augmentation to offloading will happen, but as with self-driving cars, this will take longer than expected because there are compounding layers of context and complexity. Fully autonomous AI software engineers would need to deal with an incredible amount of complexity, so we should be cautious about our expectations.

Sallam said companies need to start with the use case, then pick the tool that works best for it. For a variety of families of use cases, she showed a heat map that lists the suitability of different kinds of common AI techniques that are best-suited for those cases. No technique is perfect, she said, so many people will want to combine different AI techniques. In reality, a rush to innovate without ethical consideration can lead to long-term damage—both to brands and to society.

Campaign Middle East had an interesting conversation with Ali Ozbay, Vice President of Marketing and Communications for the All Inclusive Collection and Rixos Hotels, activating the keys to the ‘suite’ spot in hospitality marketing. Today Rachel teaches how to start freelancing and experience a thrilling career doing what you love. While you can prompt AI ChatGPT to draft well-structured bullet points, it cannot delve deep into the details of your career journey to date and unpack transferable skills and common themes which will be relevant to the roles you wish to apply for. It cannot coach you to achieve your career aspirations, or effectively help you tie your resume into your overall personal brand image.

Vant shared a personal anecdote from her time at Xero, where AI was introduced to help automate tedious financial tasks. She’s also building a product and launching a course that will revolutionize freelance work, making it easier to make money, find clients, and network with other freelancers. So I wrote an epic missive on the absurdity of AI agent overhype, hopped on a plane to Vegas, to hear UiPath make splashy news announcements about… The launch environment for pharmaceutical industry products is evolving at pace with new scientific discoveries and shifting engagement patterns, creating challenges and opportunities. Two players in medical extended reality (XR) – XRHealth and NeuroReality – have come together in a quest to build the biggest company in the sector.

“Participants shared that you need to ensure you have a modern data infrastructure that can handle both large volumes and velocities of unstructured data in conjunction with structured data,” said Chakraborty. “Knowing how to use and interact with large language models as they show various types of behavior is important,” he said. Moor Insights & Strategy provides or has provided paid services to technology companies, like all tech industry research and analyst firms. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking and video and speaking sponsorships. Of the companies mentioned in this article, Moor Insights & Strategy currently has (or has had) a paid business relationship with Accenture, AT&T, AWS, Google, IBM, Meta, Microsoft, Oracle and Zoom.

Gen AI is not a good fit for planning and optimization, prediction and forecasting, decision intelligence, and autonomous systems, Sallam said. In each of these categories, she listed examples, explained why gen AI fails in those areas, and suggested alternative techniques. She stressed that generative AI is very useful for the right use cases, but not for everything.

Kendra Vant, an AI advisor for boards and start-ups, delivered a striking reminder during the panel discussion. “AI has the power to transform industries, but it also has the potential to cause harm if not used responsibly,” she said. Her words echoed throughout the room, drawing the audience into a conversation that many tech innovators might find uncomfortable, but necessary.

The use cases need to be clear of sufficient scale to move the needle, and explicitly incorporated into the annual business plan. You can train models today using our product – and that’s a differentiator. Our document understanding is the leading, most accurate document understanding capability. We believe that’s a superpower for our agents that are going to be working on more unstructured content.

Sallam shared data from a recent survey that showed that gen AI is already the most popular technique that organizations are using in adopting AI solutions, followed by machine learning with things like regression techniques. At Gartner’s annual expo, analysts offer a deeper dive into how businesses should approach AI, from when to avoid gen AI and how to scale for a future dominated by the technology. In our industry, we often celebrate the rapid advancements in AI and tech, focusing on the flashy new features or the latest unicorn. His story also highlighted the importance of mentorship and collaboration between startups and corporates, especially in a landscape where startups might lack the resources or expertise to navigate complex ethical dilemmas on their own. The model features Design CoPilot, an interactive tool for refining designs through conversational feedback.

Unlike models driven solely by technical prompts, Recraft’s AI considers aspects like aesthetics, balance, and context, making it useful for graphic designers, product designers, and 3D modelers. This model can generate assets like 3D environments, textures, and UI elements that align closely with human creative intent while maintaining text consistency and optimal length ChatGPT App throughout the generated outputs. They claim that this is the only model in the world that can do long sentences of text and still maintain consistency. The Gemini API integration allows Vertex AI to access up-to-date information directly from Google Search, giving grounded AI models access to live, real-world data that helps generate more precise and relevant responses.